Project description:MicroRNAs (miRNA) are a class of small regulatory RNAs that mediate post-transcriptional silencing of specific target mRNAs. Data suggest the importance of miRNAs to cancer development and possibly to survival. Our overall hypothesis is that miRNA expression is unique to tumor molecular phenotype; that miRNA expression levels at time of diagnosis predicts survival; and that miRNA expression is associated with inflammation-related genetic and lifestyle factors key to colorectal cancer (CRC). This study takes a two pronged approach to addressing our hypotheses. While we propose to validate previously identified miRNAs that have been identified as associated with CRC (either by differential expression or from assessment of mutations), we will add to the field through discovery of new and important associations that may be unique to specific molecular phenotypes, to polyp to cancer progression, and to survival. We have analyzed the expression of 2006 human miRNAs using data derived from tumor and paired normal tissue at time of diagnosis from: 1975 people with incident colon cancer or rectal cancer and 290 polyps from colon and rectal cases (included in this study) who reported a prior polyp. MiRNA was obtained from dissected paraffin-embedded tissue and assessed using an Agilent microarray platform. We intend to extend our validation of previously identified mutated miRNAs and differentially expressed miRNAs to determine if these alterations are associated with specific tumor molecular phenotype (TP53, KRAS2, CIMP+, and for colon tumors MSI+), inflammation-related factors, clinical factors and survival. We will identify associations with miRNAs that are related to specific molecular phenotypes, with drivers in the carcinogenic process, and with clinical features and survival. These miRNAs will be validated using targeted Agilent Platform. Associations will be tested based on differential expression for both individual and groups of miRNAs using recent extensions of several statistical methods including ANOVA, logistic regression, and Cox proportional hazards models. Our sample size allows for both a training and validation component, and provides sufficient statistical power to meet the study goals. MiRNAs that are differentially expressed in polyps and in subsequent tumors will provide new insights into targets for screening and treatment as well as provide support that miRNAs function as the “driver” in the carcinogenic process. Testing of mutated miRNAs identified from sequencing in conjunction with tumor phenotype, clinical, and survival data will further validate the importance of these miRNAs, and provide insight as to which CRC molecular pathway the miRNAs function. Our rich dataset of lifestyle, genetic, clinical and prognosis, and tumor molecular phenotype on 1975 CRC and paired normal tissue allows us to examine factors that are associated with miRNA expression and mutation in a large sample of population-based cases in the most cost-efficient manner possible. The miRNAs identified in these analyses will elucidate pathways important in the etiology of CRC and will provide insight into potential targets for screening and treatment. MiRNAs are small, non-protein-coding RNA molecules that regulate gene expression either by post-transcriptionally suppressing mRNA translation or by mRNA degradation. We examine differentially expressed miRNAs in colorectal carcinomas, adenomas, and normal colonic mucosa. Data come from population-based studies of colorectal cancer conducted in Utah and the Kaiser Permanente Medical Care Program. A total of 1893 carcinoma/normal paired samples and 290 adenoma tissue samples were run on the Agilent Human miRNA Microarray V19.0 which contained 2006 miRNAs. We tested for significant differences in miRNA expression between paired carcinoma/adenoma/normal colonic tissue samples. Fewer than 600 miRNAs were expressed in >80% of people for colonic tissue; of these 86.5% were statistically differentially expressed between carcinoma and normal colonic mucosa using a False Discovery Rate of 0.05. Roughly half of these differentially expressed miRNAs showed a progression in levels of expression from normal to adenoma to carcinoma tissue. Other miRNAs appeared to be altered at the normal to adenoma stage, while others were only altered at the adenoma to carcinoma stage or only at the normal to carcinoma stage. Evaluation of the Agilent platform showed a high degree of repeatability (r=0.98) and reasonable agreement with the NanoString platform. Our data suggest that miRNAs are highly dysregulated in colorectal tissue among individuals with colorectal cancer; the pattern of disruption varies by miRNA as tissue progresses from normal to adenoma to carcinoma.

Project description:Claret2009 - Predicting phase III overall survival in colorectal cancer This model is described in the article: Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. Claret L, Girard P, Hoff PM, Van Cutsem E, Zuideveld KP, Jorga K, Fagerberg J, Bruno R. J. Clin. Oncol. 2009 Sep; 27(25): 4103-4108 Abstract: PURPOSE: We developed a drug-disease simulation model to predict antitumor response and overall survival in phase III studies from longitudinal tumor size data in phase II trials. METHODS: We developed a longitudinal exposure-response tumor-growth inhibition (TGI) model of drug effect (and resistance) using phase II data of capecitabine (n = 34) and historical phase III data of fluorouracil (FU; n = 252) in colorectal cancer (CRC); and we developed a parametric survival model that related change in tumor size and patient characteristics to survival time using historical phase III data (n = 245). The models were validated in simulation of antitumor response and survival in an independent phase III study (n = 1,000 replicates) of capecitabine versus FU in CRC. RESULTS: The TGI model provided a good fit of longitudinal tumor size data. A lognormal distribution best described the survival time, and baseline tumor size and change in tumor size from baseline at week 7 were predictors (P < .00001). Predicted change of tumor size and survival time distributions in the phase III study for both capecitabine and FU were consistent with observed values, for example, 431 days (90% prediction interval, 362 to 514 days) versus 401 days observed for survival in the capecitabine arm. A modest survival improvement of 39 days (90% prediction interval, -21 to 110 days) versus 35 days observed was predicted for capecitabine. CONCLUSION: The modeling framework successfully predicted survival in a phase III trial on the basis of capecitabine phase II data in CRC. It is a useful tool to support end-of-phase II decisions and design of phase III studies. This model is hosted on BioModels Database and identified by: MODEL1708310001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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MiRNA and colorectal cancer: associations with tumor phenotype and survival

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